Commit af94cabf authored by Tom Rushby's avatar Tom Rushby
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Merge branch 'openGeogRmd' into 'master'

Create Rmd and html version of ONS-open-geog

See merge request SERG/mapping-with-r!4
parents e95a29b3 a8cd8c24
---
title: "Using the ONS Open Geography API"
subtitle: "example of using the API to get feature layer data - boundaries"
author: "Tom Rushby (@tom_rushby)"
date: 'Last run at: `r Sys.time()`'
output:
bookdown::html_document2:
fig_caption: yes
code_folding: show
number_sections: yes
toc: yes
toc_depth: 4
toc_float: TRUE
bookdown::pdf_document2:
toc: yes
fig_caption: yes
number_sections: yes
bookdown::word_document2:
fig_caption: yes
number_sections: yes
toc: yes
toc_depth: 4
fig_width: 5
always_allow_html: yes
---
```{r setup, include=FALSE}
# you might need to install these first
library(sf)
library(htmltools)
library(leaflet)
library(utils)
library(dplyr)
library(knitr)
```
# Introduction
This script provides an example of downloading and importing administrative boundaries from the Office for National Statistics Open Geography portal into RStudio and plotting on a map. It is based upon a useful example by [Trafford Data Lab](https://medium.com/@traffordDataLab/pushing-the-boundaries-with-the-open-geography-portal-api-4d70637bddc3).
## Creating a query
In this example we want to load Local Authority District geography. The Open Geography portal helpfully provides an [API explorer](https://geoportal.statistics.gov.uk/datasets/ons::local-authority-districts-december-2020-uk-bgc/api) to help us structure the query.
In the code chunk below, we break up the query into parts that we can change depending on the type of geography we want, the areas we want to include, the fields we want the query to return etc.
```{r geoQueryElements}
# Elements for the query
geo_endpoint <- "https://ons-inspire.esriuk.com/arcgis/rest/services/"
# The geo boundary layer will change depending on which
geo_boundarylayer <- "Administrative_Boundaries/Local_Authority_Districts_December_2020_UK_BGC/"
geo_server <- "FeatureServer/0/"
geo_search <- "LAD20NM IN "
# Construct a vector of local authorities to load
# the following local authorities are the 'Solent' region
las_to_load <- c("Southampton","Portsmouth","Winchester",
"Eastleigh","Isle of Wight","Fareham",
"Gosport","Test Valley","East Hampshire",
"Havant","New Forest","Hart","Basingstoke and Deane")
geo_where <- las_to_load # sometimes we don't want all boundaries
geo_outfields <- "*" # returns all fields
#geo_outfields <- c("LAD20CD","LAD20NM","LONG","LAT") # use in place of line above to return selected fields only
geo_outSR <- "4326"
geo_format <- "json"
```
We then paste the elements together to construct the API query URL ...
```{r constructGeoQuery}
# Assemble the full URL for the query from elements above
geo_query_string <- paste0(geo_endpoint,geo_boundarylayer,geo_server,
"query?where=",geo_search,"(",paste(paste0("'",geo_where,"'"), collapse = ","),
")&outFields=",(paste(geo_outfields, collapse = ",")),"&outSR=",geo_outSR,"&f=",geo_format)
# Format the URL to remove spaces
geo_query <- utils::URLencode(geo_query_string)
```
```{r runQuery}
message("Loading LA geometry from ONS Open Geography API")
# API query
sf_data <- st_read(geo_query)
```
## Data returned
So what did the API query return? Table \@ref(tab:geoTable) shows selected columns from the data. The data.frame contains a row for each local authority district, with the `geometry` column containing the geography; in this case the polygon data relating to the boundary of each local authority.
```{r geoTable}
kable(sf_data[c(2:3,7:9)], caption = "Selected columns of data by API query")
```
## Checking coordinate reference system
Useful lookup spatial reference for CRS [https://spatialreference.org/](https://spatialreference.org/ref/epsg/27700/).
Sometimes transformation is required using the `st_transform()` function.
```{r checkingCRS}
st_coord_sys <- st_crs(sf_data) # check coord system
st_coord_sys # current coord system EPSG: 4326 (is what leaflet wants - good)
# transform the coord system if required
if(st_coord_sys$epsg != 4326){
sf_data <- st_transform(sf_data, "+proj=longlat +datum=WGS84")
}
```
## Create map
Now we can create a map, here using the [Leaflet package](https://rstudio.github.io/leaflet/).
Find a [cheatsheet here](https://github.com/rstudio/cheatsheets/raw/master/leaflet.pdf).
Optional: first we can create popups by adding a column to `sf_data` (uses `htmltools`).
```{r}
sf_data$popup_text <-
paste("Locial authority area code: ","<b>", sf_data$lad20cd, "</b>",
'<br/>', 'Local authority: ', '<b>', sf_data$lad20nm, '</b>', ' ') %>%
lapply(htmltools::HTML)
```
Finally we can create the map ...
```{r}
leaflet(sf_data) %>%
addTiles() %>% # Add default OpenStreetMap map tiles
addPolygons(color = "blue", fillColor = "blue", fillOpacity = 0.2, weight = 1.5, popup = ~(lad20nm), # popups clicked
label = ~(popup_text), # define labels
labelOptions = labelOptions( # label options
style = list("font-weight" = "normal", padding = "2px 2px"),
direction = "auto"),
highlight = highlightOptions(
weight = 5,
color = "#666",
fillOpacity = 0.7,
bringToFront = TRUE))
```
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